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Computational Statistics and Machine Learning (MSc) Computational Statistics and Machine Learning (MSc) University College London

University College London

Masters Degree , Machine Learning

Course Description

This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.

The programme aims to provide graduates with the foundational principles and the practical experience needed by employers in the area of machine learning and statistics. Graduates of this programme will have had the opportunity to develop their skills by tackling problems related to industrial needs or to leading-edge research.

Course Content

Compulsory modules

  • Statistical Models and Data Analysis (15 credits)
  • Supervised Learning (15 credits)
  • MSc Computational Statistics and Machine Learning Project

Optional modules

Students must choose 45 to 75 credits from these optional modules. Students can also select 15 to 45 credits from elective modules.

  • Advanced Topics in Machine Learning (15 credits)
  • Applied Machine Learning (15 credits)
  • Approximate Inference and Learning in Probabilistic Models (15 credits)
  • Graphical Models (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Inverse Problems in Imaging (15 credits)
  • Machine Vision (15 credits)
  • Multi-agent Artificial Intelligence (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)
  • Reinforcement Learning (15 credits)
  • Selected Topics in Statistics (15 credits)
  • Statistical Natural Language Processing (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

 

Entry Requirements

A minimum of an upper second-class UK Bachelor's degree in a highly quantitative subject such as computer science, statistics, mathematics, electrical engineering or the physical sciences, or an overseas qualification of an equivalent standard. Relevant work experience may also be taken into account. Students must be comfortable with undergraduate-level mathematics; in particular it is essential that the candidate will have knowledge of statistics at an intermediate undergraduate level. The candidate should also be proficient in linear algebra and multivariable calculus.

English language requirements

If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.

The English language level for this programme is: Good

Additional Information

Fee deposit: All full time students are required to pay a fee deposit of £2,000 for this programme. All part-time students are required to pay a fee deposit of £1,000.

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